> For the complete documentation index, see [llms.txt](https://developers.oxylabs.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://developers.oxylabs.io/help-center/es/datos-para-llms/do-i-have-to-manually-format-scraped-data-for-ai-workflows.md).

# ¿Tengo que formatear manualmente los datos extraídos para flujos de trabajo de IA?

Solo si quieres. [Web API](https://developers.oxylabs.io/products/web-api) puede devolver datos en formatos que los modelos pueden usar sin reformateo manual, de tres maneras.

### **Salida en Markdown**

Agrega `"output": ["markdown"]` a tu `/scrape` solicitud, y Web API devuelve el contenido de la página como Markdown. Es limpio, estructurado y fácil de leer para los LLM. Consulta la [documentación de Scrape](https://developers.oxylabs.io/products/web-api/scrape) para todas las opciones de salida.

### **JSON estructurado con análisis de IA**

Describe los datos que necesitas en lenguaje claro, o proporciona un JSON Schema, y Web API lo devuelve como JSON estructurado. Consulta la [documentación de análisis de IA](https://developers.oxylabs.io/products/web-api/scrape/ai-parsing) para más detalles.

### **servidor MCP**

Si usas un agente de IA o un asistente de programación, conéctalo a Web API a través de nuestro servidor oficial Model Context Protocol (MCP). Cualquier cliente MCP, como Claude Code o Cursor, puede entonces llamar directamente a las herramientas de search, scrape y extracción. Consulta la [documentación del servidor MCP](https://developers.oxylabs.io/ai-workflows/mcp) y [GitHub](https://github.com/oxylabs/web-api-mcp) para la configuración.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://developers.oxylabs.io/help-center/es/datos-para-llms/do-i-have-to-manually-format-scraped-data-for-ai-workflows.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
